Literature DB >> 31891652

Longitudinal monitoring of KRAS-mutated circulating tumor DNA enables the prediction of prognosis and therapeutic responses in patients with pancreatic cancer.

Fumiaki Watanabe1, Koichi Suzuki1, Sawako Tamaki1, Iku Abe1, Yuhei Endo1, Yuji Takayama1, Hideki Ishikawa1, Nao Kakizawa1, Masaaki Saito1, Kazushige Futsuhara1, Hiroshi Noda1, Fumio Konishi2, Toshiki Rikiyama1.   

Abstract

BACKGROUND: Liquid biopsies enable the detection of circulating tumor DNA (ctDNA). However, the clinical significance of KRAS-mutated ctDNA for pancreatic cancer has been inconsistent with respect to its prognostic and predictive potential. METHODS AND
FINDINGS: A total of 422 blood samples were collected from 78 patients undergoing treatments for localized and metastatic pancreatic ductal adenocarcinoma. KRAS mutation in tissues and KRAS ctDNA levels in plasma were determined by RASKET and droplet digital polymerase chain reaction. Longitudinal monitoring of KRAS ctDNA was performed to assess its significance for predicting recurrence and prognosis and for evaluating therapeutic responses to chemotherapy compared with carbohydrate antigen 19-9 (CA19-9). In 67 tumor tissues, discrepancies in point mutations of KRAS were rarely observed among individual patients, implying that one targeted point mutation of KRAS can be determined in tumor tissues prior to longitudinal blood monitoring. One-time blood assessment of KRAS-mutated ctDNA before surgery or chemotherapy was not clearly associated with recurrence and prognosis. Sequential blood monitoring was performed in 39 patients who underwent surgery for potentially resectable tumors. Increased CA19-9 levels were significantly associated with recurrence, but not prognosis (P<0.001, P = 1.0, respectively), whereas emergence of KRAS ctDNA was significantly associated with prognosis (P<0.001) regardless of recurrence. Furthermore, in 39 patients who did not undergo surgery, detection of KRAS ctDNA was a predictive factor for prognosis (P = 0.005). Multivariate analysis revealed that detection of KRAS ctDNA was the only independent prognostic factor regardless of tumor resection (hazard ratios = 54.5 for patients who underwent surgery and 10.1 for patients who did not undergo surgery; P<0.001 for both). Patients without emergence of KRAS ctDNA within 1 year after surgery showed significantly better prognosis irrespective of recurrence (P<0.001). No detection or disappearance of KRAS ctDNA within 6 months of treatment was significantly correlated with therapeutic responses to first-line chemotherapy (P<0.001). Changes in KRAS status provided critical information for the prediction of therapeutic responses.
CONCLUSIONS: Our study showed for the first time that detection of KRAS ctDNA levels within a short period enables the prediction of prognosis and therapeutic responses in patients with pancreatic cancer.

Entities:  

Mesh:

Substances:

Year:  2019        PMID: 31891652      PMCID: PMC6938323          DOI: 10.1371/journal.pone.0227366

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Pancreatic ductal adenocarcinoma (PDAC) ranks as the fourth leading cause of cancer-related mortality in the United States and Japan [1, 2]. Surgical resection is considered the only curative treatment for PDAC. As PDAC is usually diagnosed at advanced stage, up to 20% of patients are suitable for initial resection [3]. Even after curative resection, most patients will experience recurrence within a year. The 5-year survival rate for patients undergoing complete resection is only approximately 25% [4]. Neoadjuvant chemotherapy to improve the treatment efficacy of surgery for patients with resectable tumors is under trial. The probability of complete resection may be lost even with a short period of neoadjuvant chemotherapy. Treatment without surgery results in unsatisfactory outcomes and poor prognosis with a median survival of 5–9 months [4], as observed in patients with unresectable tumors; nevertheless, unnecessary surgical treatment should be avoided. Recent improvements in chemotherapy for patients with unresectable tumors have shown to prolong survival. The most effective treatment should be determined according to survival benefit for each patient; hence, an ideal predictive biomarker is required. For this purpose, carbohydrate antigen 19–9 (CA19-9) has been commonly used to establish diagnosis, assess resectability, monitor progression, and determine prognosis [5]. Despite the acceptance of the utility of CA19-9 as a valuable predictor for prognosis of PDAC, controversy remains as to the sensitivity and cutoff value of CA19-9. As an alternative to CA19-9, detection of circulating cell-free DNA in the bloodstream, known as liquid biopsy, has been considered a predictive biomarker for invasive cancers [6-10]. Cell-free DNA originates from somatic DNA that is discharged into the systemic circulation following cellular necrosis and apoptosis [11]. Droplet digital polymerase chain reaction (ddPCR) and BEAMing technology are two widely used platforms for liquid biopsy, which can discover mutant alleles in the bloodstream with a high sensitivity of 0.001–0.01% [12, 13]. The detection of mutated circulating tumor DNA (ctDNA) provides prognostic and predictive information on various cancers [14, 15]. Liquid biopsy is an ideal noninvasive tool that allows multiple tests over time and provides real-time data on changes in tumors. Furthermore, liquid biopsy enables longitudinal monitoring of mutated ctDNA. Monitoring real-time changes within the tumor reflects tumor dynamics [16]. Our previous study showed that longitudinal monitoring of mutated ctDNA indicated tumor dynamics in connection with various treatments for patients with colorectal cancer, which in-turn provided useful information for treatment determination [17]. KRAS mutations have been detected in 50% of colorectal cancers and 90% of PDAC [4, 18, 19] and the heterogeneity of KRAS mutations between primary tumor and metastasis in individual patients with PDAC is rare [20, 21], suggesting that, with respect to prognosis, circulating mutant KRAS ctDNA in the blood is a good biomarker for detecting the presence of cancer cells. In 1999, Castells et al. reported the association between poor survival and presence of KRAS mutations in plasma from patients with PDAC [22]. Later, several studies reported the feasibility of detecting circulating mutant KRAS genes in the blood of patients with PDAC, as well as the prognostic relevance of these genes [23, 24]. However, the clinical significance of KRAS-mutated ctDNA in PDAC has been inconsistent with respect to its prognostic and predictive potential [25, 26]. This inconsistency could be induced by limited points of detection of circulating mutant KRAS genes in the blood. In the past, assessments were performed at a few time points, for instance, just before and after surgery. However, longitudinal monitoring has not been attempted. In this study, we evaluated the significance of sequentially assessing KRAS ctDNA levels through longitudinal monitoring. Here, we demonstrated for the first time that detection of KRAS ctDNA levels within a short period enables the prediction of prognosis and therapeutic responses in patients with PDAC.

Methods

Patients and study design

We prospectively recruited 78 patients clinically diagnosed with localized, metastatic, and recurrent PDAC and collected 422 blood samples between June 2014 and December 2017 at Saitama Medical Center, Jichi Medical University, Japan. Schematic of patient recruitment and our study endpoints are shown in S1 Fig. Characteristics of the 39 patients who underwent surgery and 39 patients who did not are shown in S1 Table, respectively. This study is conducted as an exploratory study without calculation of sample size for primary endpoints. After surgery, signs of recurrence were confirmed based on imaging findings. At least three serial liquid biopsy samples were obtained postoperatively from patients who underwent surgery. Therapeutic response of tumors was assessed based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 [27] for routine clinical evaluation. At least two serial liquid biopsy samples were obtained from patients who did not undergo surgery. However, four patients provided only one sample each because of their death. The median follow-up time for all patients was 16.2 months. All patients provided written informed consent for the examination of their tissue and plasma and the use of their clinical data. The study protocol was approved by the research ethics committee of Jichi Medical University and conformed to the ethical guidelines of the World Medical Association Declaration of Helsinki.

Analysis of KRAS status in PDAC tissues

KRAS status in PDAC tissues was evaluated by RASKET with a sensitivity of 1–5% and ddPCR with a sensitivity of 0.01–0.1%, using formalin-fixed paraffin-embedded (FFPE) tumor tissues, including endoscopic ultrasound-guided fine-needle aspiration samples. KRAS status in 67 tumor tissues was analyzed using RASKET by a clinical testing company (Special Reference Laboratories, Tokyo, Japan). Subsequently, tissue DNA was extracted from 73 FFPE tissues using QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Early reports have shown that point mutations at codon 12 of KRAS oncogene mostly include G12V, G12D, and G12R, whereas other types of point mutations of KRAS are rarely detected in patients with PDAC [19, 28, 29]. Therefore, these three types of KRAS mutations were predominantly identified by ddPCR. In addition, Q61H, another type of KRAS mutation that emerged prior to drug resistance was verified in four patients by ddPCR after initial determination by RASKET. KRAS status in five patients could not be assessed because of insufficient DNA samples.

Analysis of heterogeneity of KRAS mutations in PDAC by ddPCR

Slices with a thickness of 10 μm were obtained for each FFPE tissue specimen from patients who underwent surgery. Deparaffinization, rehydration, and hematoxylin and eosin staining were performed under enzyme-free conditions. The slides were subsequently placed on polyethylene naphthalate membrane slides (Leica Microsystems, Wetzlar, Germany) for laser microdissection using LMD 7000 (Leica Microsystems, Wetzlar, Germany), and the tumor center and invasion front were then isolated from each slide (S2 Fig). After laser microdissection, DNA was extracted using the QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. KRAS mutations were assessed using ddPCR; available metastatic or recurrent tumors (N = 13) were also examined.

Plasma sample collection and processing

A total of 422 blood samples were collected from patients with localized, metastatic, and recurrent PDAC at Saitama Medical Center, Jichi Medical University. From each patient, 7 mL of whole blood was drawn into EDTA-containing tubes, and plasma was collected by centrifugation at 3000 × g for 20 min at 4°C, followed by centrifugation at 16000 × g for 10 min at 4°C in a fresh tube. Plasma samples were separated from peripheral blood cells and stored at -80°C until DNA extraction.

Extraction of circulating cell-free DNA

Circulating cell-free DNA was extracted from 2 mL of plasma using QIAamp Circulating Nucleic Acid Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions.

ddPCR analyses

KRAS status in tumor tissues and plasma was analyzed using the Bio-Rad QX200 ddPCR system (Bio-Rad Laboratories, Hercules, CA, USA). We used a commercially available PrimePCR KRAS kit for ddPCR. KRAS mutations in each blood sample were verified according to the corresponding mutation (C12V, G12D, G12R, and Q61H) in matched tumor tissues determined by ddPCR (S3 Fig). The reaction mixture comprised of 10 μL of 2× ddPCR Supermix, 1 μL of each reference and variant 20× Bio-Rad PrimePCR KRAS for ddPCR, and 10 μL of sample eluted from plasma in a final volume of 22 μL. The mixture was loaded onto a DG8 cartridge (Bio-Rad Laboratories, Hercules, CA, USA) with 70 μL of droplet generation oil, and the cartridge was placed into the droplet generator. The generated droplets (approximately 15000 generated droplets per well) were transferred to a 96-well reaction plate, heat-sealed with a foil lid, and subjected to thermocycling in a Veriti thermal cycler (Thermo Fisher Scientific, Waltham, MA, USA) under the following cycling conditions: 95°C for 10 min and 40 cycles at 95°C for 30 s and subsequently at 55°C for 90 s. Amplified droplets were analyzed using a QX200 droplet reader (Bio-Rad Laboratories, Hercules, CA, USA) for the fluorescent measurement of FAM and HEX probes for wild-type and mutant genes, respectively. QuantaSoft software (Bio-Rad Laboratories, Hercules, CA, USA) was used to measure the number of positive and negative droplets, and their ratio (mutated allele frequency) was fitted to a Poisson distribution to determine the target copy number/mL in the input reaction. Samples with two or more positive droplets were considered positive according to threshold values, which we previously reported [17]. For data reproducibility, analysis of KRAS status in tumor tissues and plasma was performed in duplicate or triplicate.

Statistical analysis

To assess prognosis, we measured recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS) as our endpoints. RFS was defined as the time from surgery to confirmation of recurrence based on radiological findings. PFS was defined as the time from pathological diagnosis to disease progression according to RECIST 1.1 or cancer-related mortality in treatment-naïve patients receiving chemotherapy. OS in patients who underwent surgery was defined by the time from surgery to occurrence of the event, whereas OS in patients who did not undergo surgery was defined by the time from pathological diagnosis to the occurrence of event. A Cox proportional hazards regression model was used to evaluate the association between overall mortality and other factors in univariate and multivariate analyses. The following variables were analyzed in patients who underwent surgery: sex; age at surgery (≤70 years versus >70 years); neoadjuvant chemotherapy (yes versus no); surgical methods (subtotal stomach-preserving pancreaticoduodenectomy and total pancreatectomy versus distal pancreatectomy); tumor size (≤2 cm versus >2 cm); pathological differentiation (well versus moderate and others); American Joint Committee on Cancer (AJCC) T factor (T1+T2 versus T3+T4); lymph node metastasis (negative versus positive); AJCC stage (IA/IB/IIA versus IIB/III/IV); preoperative CA19-9 level (≥37 U/mL versus <37 U/mL); presence of KRAS-mutated ctDNA before surgery (negative versus positive); and emergence of KRAS-mutated ctDNA and CA19-9 levels upon longitudinal monitoring. Additionally, the following variables were analyzed in patients who did not undergo surgery: sex; age (≤70 years versus >70 years); AJCC stage (III versus IV); CA19-9 level (≥37 U/mL versus <37 U/mL); presence of KRAS-mutated ctDNA (negative versus positive). RFS, PFS and OS curves were constructed using the Kaplan-Meier method. The emergence of KRAS-mutated ctDNA and CA19-9 levels were regarded as time-dependent covariates in longitudinal monitoring. To graphically illustrate the effects of KRAS-mutated ctDNA and CA19-9 on OS, Simon–Makuch plots were generated with a landmark placed at the median point of detection of KRAS-mutated ctDNA and CA19-9 >37 U/mL in patients who did and did not undergo surgery. Several factors with a P-value of <0.15 in univariate analysis were subjected to multivariate analysis. A P-value of 0.05 was considered statistically significant. Fisher’s exact test was used for categorical variables such as the presence of KRAS-mutated ctDNA, CA19-9 level (≥37 U/mL versus <37 U/mL), and outcome (dead or alive). All statistical analyses were performed using EZR version 1.31 (Saitama Medical Center, Jichi Medical University, Saitama, Japan). We also used R version 3.1.1 (The R Foundation for Statistical Computing, Vienna, Austria) for graphical interface.

Results

KRAS assessment in tumor tissue samples and investigation of heterogeneity

In advance of the investigation of KRAS-mutated ctDNA in plasma, KRAS assessment was performed in tumor tissues of 67 patients with PDAC using RASKET with a sensitivity of 1–5% and ddPCR with a sensitivity of 0.01–0.1%. With respect to frequency, G12V, G12D, D12R, Q61H, G12V+G12R, and G12D+G12R and wild-type KRAS alleles were detected in 24 (35.8%), 22 (32.8%), 6 (9.0%), 4 (6.0%), 2 (3.0%), 1 (1.5%), and 8 (11.9%) out of 67 samples, respectively. Of 67 patients, 59 (88.1%) with KRAS mutation (assigned from No. 1 to No. 59) and 8 (11.9%) patients without (assigned from No. 60 to No. 67) were identified by KRAS assessment using RASKET (S3 Fig). These 8 patients without KRAS mutation detected by RASKET showed the presence of KRAS mutations by ddPCR. KRAS mutations in these 8 patients were present at less than 1%, but ddPCR identified these rare mutations because of its high sensitivity. When the KRAS-mutated allele frequency was ≥1% based on ddPCR, the KRAS mutations detected by RASKET were identical to those by ddPCR; as observed in the 59 patients whose mutations identified by RASKET corresponded to those determined by ddPCR (S3 Fig). Moreover, we investigated the heterogeneity of KRAS mutations between tumor center and invasion front, as well as between primary tumor and metastasis, which revealed that discrepancies in KRAS status among individual patients were rarely observed. For KRAS mutations with frequency ≥1%, the concordance between tumor center and invasion front and between primary tumor and metastasis was 94.7% and 90.9%, respectively, implying the absence of heterogeneity in KRAS mutations (S4 Fig). Thus, point mutations identified in tissues should be monitored and detected in blood with no additional exploration required.

One-point assessment of KRAS ctDNA and CA19-9 levels before surgery was not associated with RFS, but KRAS ctDNA before chemotherapy was a potential predictive prognostic factor, whereas CA19-9 prior to chemotherapy was not

We evaluated the significance of one-point assessment in KRAS ctDNA and CA19-9 levels before treatments, surgery and chemotherapy, to predict treatment outcome. Among 39 patients who underwent surgery, KRAS-mutated ctDNA was detected in 7 patients, and 28 patients had CA19-9 >37 U/mL. There was no significant difference in RFS by neither KRAS-mutated ctDNA status nor CA19-9 level (P = 0.38, P = 0.7, respectively; Fig 1A). No effect of the presence of KRAS-mutated ctDNA or CA19-9 level before surgery on RFS (median: 16.9 versus 32.4 months and 16.9 versus 17.1 months, respectively; Fig 1A) was observed. With respect to one-point assessment before chemotherapy, 26 chemotherapy-naïve patients were assessed before first-line chemotherapy among 39 patients who did not undergo surgery. KRAS-mutated ctDNA was detected in 12 patients, and 20 patients had CA19-9 >37 U/mL. Although there was no significant difference in prognosis by neither KRAS-mutated ctDNA status nor CA19-9 level (P = 0.07, P = 0.86, respectively; Fig 1B), the presence of KRAS-mutated ctDNA before chemotherapy was a potential predictive prognostic factor. The median OS of patients with and without detection of KRAS-mutated ctDNA was 15.8 and 33.7 months, respectively, whereas the median OS of patients with CA19-9 level ≥37 U/mL and <37 U/mL was 16.6 and 19.8 months, respectively (Fig 1B).
Fig 1

One-point assessment of ctDNA and carbohydrate antigen 19–9 (CA19-9) before treatment to assess recurrence and prognosis.

(A) Recurrence-free survival (RFS) curves according to the presence of KRAS-mutated ctDNA and CA19-9 level before surgery in 39 patients who underwent surgery (P = 0.38 and 0.7 by log-rank test). (B) Overall survival (OS) curves according to the presence of KRAS-mutated ctDNA and CA19-9 level before first-line chemotherapy in 26 chemotherapy-naïve patients who did not undergo surgery (P = 0.07 and 0.86 by log-rank test). X-axes indicate the months from surgery, whereas Y-axes indicate the probability of RFS or OS.

One-point assessment of ctDNA and carbohydrate antigen 19–9 (CA19-9) before treatment to assess recurrence and prognosis.

(A) Recurrence-free survival (RFS) curves according to the presence of KRAS-mutated ctDNA and CA19-9 level before surgery in 39 patients who underwent surgery (P = 0.38 and 0.7 by log-rank test). (B) Overall survival (OS) curves according to the presence of KRAS-mutated ctDNA and CA19-9 level before first-line chemotherapy in 26 chemotherapy-naïve patients who did not undergo surgery (P = 0.07 and 0.86 by log-rank test). X-axes indicate the months from surgery, whereas Y-axes indicate the probability of RFS or OS.

Sequential assessments of ctDNA and CA19-9 in longitudinal monitoring to assess treatment outcome

Fig 2 shows sequential assessments of ctDNA and CA19-9 in longitudinal tests with respect to recurrence and prognosis. Fig 2A presents a comparison of KRAS-mutated ctDNA and CA19-9 in longitudinal tests for 39 patients who underwent surgery. Twenty-two patients showed recurrence and Fisher’s exact test indicated that increased CA19-9 levels were significantly associated with recurrence (P<0.001). However, increased CA19-9 levels were not linked to prognosis (P = 1.0). On the other hand, emergence of KRAS ctDNA in longitudinal tests was associated with prognosis (P<0.001) regardless of recurrence, which emphasized its significance as a prognostic factor. Fig 2B presents a comparison of KRAS-mutated ctDNA and CA19-9 in longitudinal evaluation of 39 patients who did not undergo surgery. Fisher’s exact test indicated that detection of KRAS-mutated ctDNA in longitudinal tests was associated with prognosis (P = 0.005), whereas CA19-9 was not (P = 0.692). Details on the clinical course of 39 patients who underwent surgery and 39 patients who did not are shown in S2 and S3 Tables, respectively. To demonstrate the significance of KRAS-mutated ctDNA monitoring, we present two cases of patients (one who underwent surgery and one who did not) exhibiting tumor dynamics in S5 Fig.
Fig 2

Sequential assessments of KRAS-mutated ctDNA and carbohydrate antigen 19–9 (CA19-9) level in longitudinal tests.

(A) CA19-9 levels and the emergence of KRAS-mutated ctDNA are shown under “CA19-9” and “KRAS-mutated ctDNA,” respectively, and are ordered as per the timing of blood examination after surgery (1→12). CA19-9 ≤37 U/mL and no detection of KRAS-mutated ctDNA are represented in blue, whereas CA19-9 >37 U/mL and the emergence of KRAS-mutated ctDNA are represented in red. Recurrence is shown under “Rec,” with “no” and “yes” indicated in white and gray, respectively. Prognosis is shown under “Outcome,” with “alive” and “death” indicated in white and gray, respectively. Examination results for every 3 months are shown in one cell; thus, four cells correspond to approximately 1 year. ND, not determined. (B) Sequential assessments of KRAS-mutated ctDNA and CA19-9 levels in longitudinal tests for patients who did not undergo surgery. CA19-9 levels and the emergence of KRAS-mutated ctDNA are ordered as per the timing of blood examination (1→15). Number of patients corresponds to those described in S2 and S3 Tables.

Sequential assessments of KRAS-mutated ctDNA and carbohydrate antigen 19–9 (CA19-9) level in longitudinal tests.

(A) CA19-9 levels and the emergence of KRAS-mutated ctDNA are shown under “CA19-9” and “KRAS-mutated ctDNA,” respectively, and are ordered as per the timing of blood examination after surgery (1→12). CA19-9 ≤37 U/mL and no detection of KRAS-mutated ctDNA are represented in blue, whereas CA19-9 >37 U/mL and the emergence of KRAS-mutated ctDNA are represented in red. Recurrence is shown under “Rec,” with “no” and “yes” indicated in white and gray, respectively. Prognosis is shown under “Outcome,” with “alive” and “death” indicated in white and gray, respectively. Examination results for every 3 months are shown in one cell; thus, four cells correspond to approximately 1 year. ND, not determined. (B) Sequential assessments of KRAS-mutated ctDNA and CA19-9 levels in longitudinal tests for patients who did not undergo surgery. CA19-9 levels and the emergence of KRAS-mutated ctDNA are ordered as per the timing of blood examination (1→15). Number of patients corresponds to those described in S2 and S3 Tables.

Univariate and multivariate analyses of OS

Table 1 presents the 13 independent demographic and clinicopathological variables used in univariate analysis for OS of patients who underwent surgery. Four variables—namely, neoadjuvant chemotherapy, pathological differentiation, CA19-9 levels, and emergence of KRAS-mutated ctDNA were identified as prognostic factors. Multivariate Cox proportional hazards regression model indicated that the emergence of KRAS-mutated ctDNA (hazard ratio = 54.5, confidence interval: 6.64–447.6, P<0.001) was a significant factor for survival in patients who underwent surgery (Table 1). Considering the small number in this analysis, multivariate analysis for two time-dependent factors was not feasible; hence, CA19-9 was excluded from the analysis. To graphically illustrate the effects of KRAS-mutated ctDNA and CA19-9 in longitudinal analyses on OS, Simon–Makuch plots were constructed with a landmark placed at the median time point (approximately 8 months and approximately 4 months, respectively) of the emergence of KRAS-mutated ctDNA and CA19-9 >37 U/mL (Fig 3A and 3B). Table 2 presents 6 independent demographic and clinicopathological variables used in univariate analysis for OS of patients who did not undergo surgery. In univariate analysis, the emergence of KRAS-mutated ctDNA was identified as one of the prognostic factors. Multivariate Cox proportional hazards regression model indicated that the emergence of KRAS-mutated ctDNA (hazard ratio = 10.4, confidence interval: 2.95–37.0, P<0.001) was the only significant factor for survival in patients who did not undergo surgery (Table 2). To graphically illustrate the effects of KRAS-mutated ctDNA and CA19-9 on OS, Simon–Makuch plots were generated with a landmark placed at the median time point (approximately 2 months) of the detection of KRAS-mutated ctDNA in patients who did not undergo surgery (Fig 3C). CA19-9 was not used to construct a survival curve with a time-dependent covariate, because most initial values of CA19-9 were over 37 U/mL.
Table 1

Univariate and multivariate analyses of overall survival in patients who underwent surgery.

Univariate analysisMultivariate analysis
Prognostic factorsHazard ratio (95% CI)P-valueHazard ratio (95% CI)P-value
Sex
    Male1Reference
    Female0.76 (0.26–2.21)0.61
Age at surgery (median, 69.5 years)
    <70 years1Reference
    ≥70 years1.31 (0.45–3.80)0.62
Neoadjuvant chemotherapy
    No1Reference1Reference
    Yes3.10 (0.82–11.7)0.090.62 (0.13–2.85)0.53
Operation methods
    SSPPD and total pancreatectomy1Reference
    Distal pancreatectomy0.72 (0.24–2.21)0.57
Tumor size
    ≤2 cm1Reference
    >2 cm2.98 (0.66–13.5)0.16
Pathological differentiation
    Well1Reference1Reference
    Moderate and othersa4.12 (1.38–12.3)0.011.93 (0.57–6.49)0.29
AJCC T factor
    T1/T21Reference
    T3/T43.05 (0.397–23.37)0.28
Lymph node metastasis
    Negative1Reference
    Positive0.81 (0.28–2.33)0.69
AJCC stage
    IA/IB/IIA1Reference
    IIB/III/IV0.81 (0.27–2.33)0.69
Preoperative CA19-9 level
    ≤37 U/mL1Reference
    >37 U/mL0.99 (0.31–3.16)0.98
Presence of ctDNA before surgery
    Negative1Reference
    Positive0.66 (0.14–3.0)0.58
CA19-9 status in monitoring9.4 (1.23–72.2)0.03
Emergence of ctDNA in monitoring57.2 (7.4–442.4)<0.00154.5 (6.64–447.6)<0.001

aOthers include poorly, scirrhous, and adenosquamous; CI, confidence interval; SSPPD, subtotal stomach-preserving pancreaticoduodenectomy; AJCC, American Joint Committee on Cancer; CA19-9, carbohydrate antigen 19–9; ctDNA, circulating tumor DNA.

Fig 3

Outcome according to KRAS-mutated ctDNA and CA19-9 in longitudinal evaluations.

(A) Simon–Makuch plot for the effect of emergence of KRAS-mutated ctDNA on overall survival (OS) in patients who underwent surgery, illustrated by a landmark at 8 months, the median time point for the detection of KRAS-mutated ctDNA (P<0.001). (B) Simon–Makuch plot for the effect of CA19-9 level on OS in patients who underwent surgery, illustrated by a landmark at 4 months, the median time point for CA19-9 level increasing to >37 U/mL (P = 0.03). (C) Simon–Makuch plot for the effect of emergence of KRAS-mutated ctDNA on OS in patients who did not undergo surgery, illustrated by a landmark at 2 months, the median time point for the detection of KRAS-mutated ctDNA (P<0.001). X-axes in Fig 3A and 3B indicate the months from surgery, X-axis in Fig 3C indicates the months from the initial evaluation in this study, whereas Y-axes indicate the probability of survival.

Table 2

Univariate and multivariate analyses of overall survival in patients who did not undergo surgery.

Univariate analysisMultivariate analysis
Prognostic factorsHazard ratio (95% CI)P-valueHazard ratio (95% CI)P-value
Sex
    Male1Reference
    Female0.82 (0.38–1.78)0.61
Age (median, 69.5 years)
    <70 years1Reference
    ≥70 years1.73 (0.80–3.71)0.16
AJCC stage
    Stage III1Reference
    Stage IV1.27 (0.55–2.92)0.58
CA19-9 levela
    ≤37 U/mL1Reference
    >37 U/mL1.02 (0.45–2.28)0.97
Presence of ctDNAa
    Negative1Reference
    Positive2.12 (0.99–4.57)0.050.55 (0.22–1.39)0.21
Emergence of ctDNA in monitoring6.75 (2.23–19.9)<0.00110.4 (2.95–37.0)<0.001

aInitial evaluation in monitoring; CI, confidence interval; AJCC, American Joint Committee on Cancer; CA19-9, carbohydrate antigen 19–9; ctDNA, circulating tumor DNA.

Outcome according to KRAS-mutated ctDNA and CA19-9 in longitudinal evaluations.

(A) Simon–Makuch plot for the effect of emergence of KRAS-mutated ctDNA on overall survival (OS) in patients who underwent surgery, illustrated by a landmark at 8 months, the median time point for the detection of KRAS-mutated ctDNA (P<0.001). (B) Simon–Makuch plot for the effect of CA19-9 level on OS in patients who underwent surgery, illustrated by a landmark at 4 months, the median time point for CA19-9 level increasing to >37 U/mL (P = 0.03). (C) Simon–Makuch plot for the effect of emergence of KRAS-mutated ctDNA on OS in patients who did not undergo surgery, illustrated by a landmark at 2 months, the median time point for the detection of KRAS-mutated ctDNA (P<0.001). X-axes in Fig 3A and 3B indicate the months from surgery, X-axis in Fig 3C indicates the months from the initial evaluation in this study, whereas Y-axes indicate the probability of survival. aOthers include poorly, scirrhous, and adenosquamous; CI, confidence interval; SSPPD, subtotal stomach-preserving pancreaticoduodenectomy; AJCC, American Joint Committee on Cancer; CA19-9, carbohydrate antigen 19–9; ctDNA, circulating tumor DNA. aInitial evaluation in monitoring; CI, confidence interval; AJCC, American Joint Committee on Cancer; CA19-9, carbohydrate antigen 19–9; ctDNA, circulating tumor DNA.

Sequential assessments of ctDNA within 1 year to assess prognosis in patients who underwent surgery

As presented in Fig 2A, patients demonstrating emergence of ctDNA within 1 year after surgery showed poor prognosis regardless of recurrence after surgery; hence, we re-evaluated the outcome by comparing patients with emergence of ctDNA within 1 year to patients without emergence. A statistically significant difference in OS according to KRAS status in blood was observed (P<0.001; Fig 4A). The emergence of KRAS-mutated ctDNA within 1 year after surgery was significantly associated with worse OS (median: not applicable versus 13.4 months).
Fig 4

Sequential assessments of KRAS-mutated ctDNA within a short period to assess outcome.

(A) Overall survival (OS) curves according to the emergence of KRAS-mutated ctDNA within 1 year after surgery (P<0.001 by log-rank test). (B) Progression-free survival (PFS) curves according to the emergence of KRAS-mutated ctDNA within 6 months of chemotherapy (P<0.001 by log-rank test). X-axes indicate the months from surgery and diagnosis, whereas Y-axes indicate the probability of OS and PFS.

Sequential assessments of KRAS-mutated ctDNA within a short period to assess outcome.

(A) Overall survival (OS) curves according to the emergence of KRAS-mutated ctDNA within 1 year after surgery (P<0.001 by log-rank test). (B) Progression-free survival (PFS) curves according to the emergence of KRAS-mutated ctDNA within 6 months of chemotherapy (P<0.001 by log-rank test). X-axes indicate the months from surgery and diagnosis, whereas Y-axes indicate the probability of OS and PFS.

Sequential assessments of ctDNA within 6 months to assess therapeutic responses of chemotherapy-naïve patients

To evaluate therapeutic responses, we recruited 26 chemotherapy-naïve patients. Drug response was assessed using RECIST within 6 months of chemotherapy. A statistically significant difference in PFS was observed between patients in whom KRAS-mutated ctDNA was detected and those in whom KRAS-mutated ctDNA was not detected or disappeared within 6 months of chemotherapy (P<0.001; Fig 4B). The emergence of KRAS-mutated ctDNA within 6 months of chemotherapy was significantly associated with worse PFS (median: 14.9 versus 4.8 months). Changes in KRAS status provided critical information for the prediction of therapeutic responses. However, an analysis of patients according to CA19-9 levels to construct a survival curve for assessing therapeutic responses was not performed because CA19-9 did not show any change during treatments.

Discussion

Our study showed the significance of sequential KRAS ctDNA assessments for predicting prognosis and therapeutic responses in patients with PDAC via longitudinal monitoring. In contrast, one-time assessment of KRAS-mutated ctDNA before surgery or chemotherapy was not clearly associated with recurrence and prognosis. Longitudinal monitoring of KRAS-mutated ctDNA enabled us to inform predictive significance within a short period after initial monitoring. Patients without emergence of KRAS ctDNA within 1 year after surgery showed significantly better prognosis irrespective of recurrence (P<0.001). No detection or disappearance of KRAS ctDNA within 6 months of treatment was significantly correlated with therapeutic responses to first-line chemotherapy (P<0.001). Changes in KRAS status provided critical information towards prediction of therapeutic responses. Our study showed for the first time that assessment of KRAS-mutated ctDNA within a short period enables the prediction of prognosis and therapeutic responses in patients with PDAC. With respect to heterogeneity, molecular heterogeneity within the primary tumor (intratumoral heterogeneity) and between the primary tumor and metastatic lesions has been described previously [30-33] and is associated with resistance to various treatments [34]. Some studies have reported discrepancies between the primary tumor and KRAS-mutated ctDNA [6, 35, 36]. Hashimoto et al. [20] reported that intratumoral heterogeneity was observed in KRAS mutations between tumor centers and invasion fronts in 4.1% patients with pancreatic cancer. Makohon-Moore et al. [21] detected identical mutations in driver genes such as KRAS and SMAD4 and reported no discrepancy in driver genes between primary tumors and distant metastases. In context of this controversy, we investigated the heterogeneity of KRAS mutations in PDAC in advance. The concordance between tumor center and invasion front and between primary tumor and metastasis was more than 90.0%; thus, the types of mutations detected in tissues were investigated by ddPCR in the blood. Discrepancies in point mutations of KRAS were rarely observed among individual patients, implying that a targeted point mutation of KRAS can be determined in tumor tissues prior to longitudinal monitoring of blood. In our study, the presence of KRAS-mutated ctDNA before surgery was not clearly associated with recurrence. No report has addressed the significant effect of KRAS-mutated ctDNA on RFS, suggesting that one-point assessment of KRAS-mutated ctDNA before surgery was not useful for predicting recurrence. Nonetheless, with respect to prognosis prediction, Hadano et al. reported that one-point assessment of ctDNA before surgery was associated with patient outcome [37]. In patients who did not undergo surgery, KRAS-mutated ctDNA was likely associated with prognosis. Two studies supported our data [25, 26], but they could not demonstrate the significance of KRAS-mutated ctDNA for prognosis prediction. In contrast, preoperative CA19-9 levels showed no association with RFS, and CA19-9 levels in patients who did not undergo surgery were not associated with OS. Different CA19-9 thresholds were reported to predict RFS or OS [38, 39]; therefore, the optimal cut-off value of CA19-9 needs further investigation. Longitudinal monitoring of KRAS-mutated ctDNA is a great advantage of liquid biopsy. In our study, multiple testing over time enabled the evaluation of association between the presence of KRAS-mutated ctDNA and prognosis of PDAC irrespective of tumor resection. A literature search for relevant studies using the search terms “circulating DNA” and “pancreatic cancer” was conducted in PubMed, and 18 studies investigating KRAS-mutated ctDNA in patients with PDAC were identified. In their review, Gall et al. [40] reported a similar number of studies describing KRAS-mutated ctDNA in patients with PDAC. Thus far, studies on this subject remain few. Furthermore, except for our study and those of Bernard et al. [41] and Sausen et al. [42], few have addressed the importance of longitudinal monitoring for predicting the outcome of PDAC. Bernard et al. reported the usefulness of patients’ exosome DNA in addition to KRAS-mutated ctDNA in PDAC. Considering the advantages of monitoring, they concluded that serial exosome DNA was significantly associated with eventual disease progression; in contrast, serial KRAS-mutated ctDNA was not significantly correlated with the presence or absence of progression. In our study, emergence of KRAS-mutated ctDNA was considered a time-dependent covariate in longitudinal monitoring, and its effect with respect to prognosis was shown for the first time. In addition, CA19-9 level was identified as a prognostic factor in patients who underwent surgery in univariate analysis; nonetheless, CA19-9 was not regarded as a time-dependent covariate because most baseline CA19-9 values were >37 U/mL. We observed a change in KRAS status in blood of a patient who exhibited complete radiological response to chemotherapy. KRAS-mutated ctDNA disappeared in response to drug treatment. We evaluated therapeutic responses to chemotherapy by comparing patients in whom KRAS-mutated ctDNA was detected to patients in whom KRAS-mutated ctDNA was not detected or disappeared within 6 months of chemotherapy. The change in KRAS status in blood enabled us to demonstrate that KRAS status was associated with PFS. These results are congruent with those reported by Del Re et al. [25] and Kruger et al. [43] who showed that early changes in KRAS-mutated ctDNA levels were useful for monitoring treatment responses in patients with PDAC. Moreover, longitudinal monitoring revealed the significance of KRAS mutation assessment within 1 year after surgery, which was strongly associated with outcome irrespective of recurrence. Patients in whom KRAS-mutated ctDNA was not detected within 1 year after surgery showed better prognosis and responded significantly better to chemotherapy even after recurrence. These findings suggest the significance of sequential assessment of KRAS-mutated ctDNA within a short period. In conclusion, our study demonstrated for the first time that assessment of KRAS-mutated ctDNA using longitudinal evaluation enables the prediction of prognosis and therapeutic responses in patients with PDAC. Although our study results should be interpreted within the study limitations and further examinations are required to draw a definitive conclusion, we believe that our study casts greater light on the selection of patients with PDAC.

Schematic of patient recruitment and our study endpoints.

(TIF) Click here for additional data file.

Representative tumor centers (TC) and invasion fronts (IF).

(TIF) Click here for additional data file.

Comparison of KRAS status in tumor tissues using RASKET and droplet digital polymerase chain reaction (ddPCR).

KRAS mutations by RASKET and ddPCR are indicated in red, KRAS mutations with frequencies <1% by ddPCR are displayed in pink, and wild types are presented in aqua. Blank indicates no detection of KRAS mutation. ND, not determined. (TIF) Click here for additional data file.

Comparison of KRAS mutations within the primary tumor (intratumoral heterogeneity) and between the primary tumor and metastatic lesions.

(A) Assessment of KRAS mutations between tumor center and invasion front using droplet digital polymerase chain reaction (ddPCR). KRAS mutations with frequencies ≥1% are indicated in red, whereas those with frequencies <1% are displayed in pink. Blank indicates no detection of KRAS mutation. ND, not determined. As for KRAS mutations with frequencies ≥1%, 36 tumors showed concordance between the tumor center and invasion front, accounting for 94.7%. Two tumors (no. 24 and no. 63) did not show concordance; the number of tumors corresponded to that presented in S3 Fig (B) KRAS mutations with frequencies ≥1% are indicated in red, whereas those with frequencies <1% are displayed in pink. Blank indicates no detection of KRAS mutation. ND, not determined; LN, lymph node; Local, local recurrence in residual pancreas. As for KRAS mutations with frequencies ≥1%, 10 tumors showed concordance between the primary tumor and metastasis, accounting for 90.9%. One tumor (no. 27) did not show concordance; the number of tumors corresponded to that presented in S3 Fig. (TIF) Click here for additional data file.

Clinical course of representative patients in longitudinal assessments.

(A) A patient underwent subtotal stomach-preserving pancreaticoduodenectomy for pancreatic head cancer and was treated with S1 as adjuvant chemotherapy. CT image is shown (a). KRAS-mutated ctDNA increased in advance of CA19-9, and potential lymph node recurrence was subsequently detected using CT imaging. Following identification of recurrence by CT imaging (b, white arrowhead), first-line treatment with nab-paclitaxel temporarily led to tumor shrinkage (c) but eventually resulted in death. X-axes indicate the days from surgery, whereas Y-axes indicate the CA19-9 value and mutated allele level. (B) A patient with pancreatic body cancer and para-aortic lymph node metastasis (d, yellow arrow and arrowhead), the pathological diagnosis of which was established by fine-needle aspiration biopsy, was treated with FOLFIRINOX as first-line chemotherapy. KRAS-mutated ctDNA decreased and disappeared after chemotherapy. However, 17 cycles of FOLFIRINOX led to peripheral neuropathy; thus, the regimen was discontinued and FOLFIRI was used for this patient. Positron emission tomography (PET) revealed an absence of accumulation in the pancreatic body and para-aortic lymph node (e, yellow arrow and arrowhead), suggesting complete response. X-axes indicate the days from surgery, whereas Y-axes indicate the CA19-9 value and mutated allele level. FOLFIRINOX, folinic acid, fluorouracil, irinotecan, and oxaliplatin; FOLFIRI, folinic acid, fluorouracil, and irinotecan. (TIF) Click here for additional data file. A) Characteristics of patients who underwent surgery. B) Characteristics of patients who did not undergo surgery. (DOC) Click here for additional data file.

Clinical information of patients who underwent surgery.

(DOC) Click here for additional data file.

Clinical information of patients who did not undergo surgery.

(DOC) Click here for additional data file.

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present. 22 Aug 2019 PONE-D-19-17596 Longitudinal monitoring of KRAS-mutated circulating tumor DNA enables the prediction of prognosis and therapeutic responses in patients with pancreatic cancer PLOS ONE Dear Dr. Suzuki, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised below by the reviewers during the review process. We would appreciate receiving your revised manuscript by Oct 06 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'. Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out. We look forward to receiving your revised manuscript. Kind regards, Surinder K. Batra Academic Editor PLOS ONE Journal Requirements: 1. When submitting your revision, we need you to address these additional requirements. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. In the Methods, please provide a justification of the sample size used in this study. 3. Our staff editors have determined that your manuscript is likely within the scope of our Targeted Anticancer Therapies and Precision Medicine Call for Papers. This editorial initiative is headed by a team of Guest Editors for PLOS ONE: Andrew Cherniack, Anette Duensing, Steven Gray, Sunil Krishnan, Chandan Kumar-Sinha and Gayle Woloschak. The Collection will encompass a diverse range of research articles about the identification and classification of driver genes and somatic alterations, target and drug discovery, mechanisms of drug resistance, and early detection and screening.  Additional information can be found on our announcement page: https://collections.plos.org/s/targeted-anticancer-therapies. If you would like your manuscript to be considered for this collection, please let us know in your cover letter and we will ensure that your paper is treated as if you were responding to this call. If you would prefer to remove your manuscript from collection consideration, please specify this in the cover letter. 4. Thank you for stating that “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript” in your financial disclosure. Please also provide the name of the funders of this study (as well as grant numbers if available) in your financial disclosure statement. 3. Thank you stating the following in your competing interests statement: "“The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript”" Please complete the competing interests section fully.  If NO authors have competing interests, please enter: "The authors have declared that no competing interests exist." If Authors have competing interests please enter competing interest details beginning with this statement: "I have read the journal's policy and the authors of this manuscript have the following competing interests: [insert competing interests here]" Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf. Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Partly Reviewer #2: Yes ********** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: No Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: 1. The abstract submitted here is previously published in JCO by the same group and available online[DOI: 10.1200/JCO.2019.37.15_suppl.e15712 Journal of Clinical Oncology 37, no. 15_suppl]. therefore, to avoid self plagiarism, the abstract in the present manuscript need to be modified. 2. There are several repetition of sentences in the manuscript, e.g. [line 412-415] Hadano et al. reported that one-point assessment of ctDNA before surgery was associated with 412 patient outcome[37]. reported that one-point assessment of ctDNA before surgery was associated 413 with patient outcome. In patients who did not undergo surgery, KRAS-mutated ctDNA was likely 414 associated with prognosis. Reviewer #2: Important and timely topic; however, the authors need to rewrite major portions of the discussion and overstate that they were the first group to report this finding: Bernard et al. Gastroenterology. 2019 January ; 156(1): 108–118.e4. doi:10.1053/j.gastro.2018.09.022. Several additional relevant papers are cited in this manuscript. The Bernard paper along with many of the additional papers should be incorporated into the discussion so that the current study is put into proper context. Minor comments. Line 81. Are you suggesting that delay in surgical resection while receiving neoadjuvant therapy was responsible for the tumor becoming unresectable? I think it is more likely that the patient was spared an unnecessary surgery since it is more likely that micrometastatic disease was present at time of diagnosis. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step. Submitted filename: paper review Plos One.docx Click here for additional data file. Submitted filename: CTDNAPDACoutcomes.pdf Click here for additional data file. 18 Nov 2019 Responses to Reviewers’ Comments General comments: The article entitled “longitudinal monitoring of KRAS-mutated circulating tumor DNA enables the prediction of prognosis and therapeutic responses in patients with pancreatic cancer” describes the significance of mutated KRAS ctDNA as a prognostic marker in the liquid biopsy samples of pancreatic cancer patients. I appreciate the efforts from the authors for performing the in-depth analysis. Because the similar work has been published previously with some of the closely matching conclusions, the submitted manuscript need to be redrafted before considering it for publication. In addition, there are major concerns related to manuscript writing, reference citation, and plagiarism. If considered for publication, following are my comments that need to be addressed: Major comments: 1. Although the study has been performed on a bigger cohort of PC patients and include the longitudinal analysis of liquid biopsy samples, authors need to justify how the submitted manuscript is different than the previously published research on prognostic significance of mutKRAS ctDNA in PC patients. following are the references for similar kind of work: • Kruger, S., et al., Repeated mutKRAS ctDNA measurements represent a novel and promising tool for early response prediction and therapy monitoring in advanced pancreatic cancer. Ann Oncol, 2018. 29(12): p. 2348-2355. We are in agreement the editor’s suggestion. Kruger et al. reported that a decrease in mutKRAS ctDNA levels during therapy was an early indicator of response to therapy during the first 4 weeks of treatment. In accordance with the reviewer’s suggestion, we have revised the manuscript as follows: Discussion section, lines 404-406 “These results are congruent with those reported by Del Re et al. [25] and Kruger et al. [43] who showed that early changes in KRAS-mutated ctDNA levels were useful for monitoring treatment responses in patients with PDAC.” • Cohen, J.D., et al., Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers. Proceedings of the National Academy of Sciences, 2017. 114(38): p. 10202. Cohen et al. aimed to detect the early stage of pancreatic cancer by combined circulating tumor DNA and protein biomarker-based liquid biopsy. The aim of their study is slightly different from the purpose of our study; hence, this paper was not cited in our manuscript. • Tjensvoll, K., et al., Clinical relevance of circulating KRAS mutated DNA in plasma from patients with advanced pancreatic cancer. Molecular Oncology, 2016. 10(4): p. 635-643. In the study by Tjensvoll et al., Kaplan–Meier survival analyses indicated that patients with positive ctDNA status before or after initiation of chemotherapy had shorter progression-free survival, albeit without statistical significance. 2. The abstract has been previously published in JCO and content has been copied in the submitted manuscript. It will be considered as self-plagiarism and therefore, authors are requested to modify the abstract [DOI: 10.1200/JCO.2019.37.15_suppl.e15712 Journal of Clinical Oncology 37, no. 15_suppl]. In view of your valuable comment, we have accordingly revised the abstract and modified it in a different form. 3. Authors focused on comparative analysis of mutKRAS ctDNA and CA19-9 in liquid biopsy samples ignoring their combined sensitivity in prediction of prognosis. Previous study by Cohen et al., 2017 in PNAS states that combination of ctDNA and protein-based markers increases the sensitivity. Cohen et al. focused on detecting the early stage of pancreatic cancer by combined circulating tumor DNA and protein biomarker-based liquid biopsy. Our study aimed to evaluate the usefulness of KRAS ctDNA monitoring for the prediction of prognosis and therapeutic responses in patients with pancreatic cancer. 4. The references are neither updated nor cited appropriately, e.g. ref 01 is about pancreatic cancer statistics and it was published in 2009, although 2019 cancer statistics is available. I apologize for the inappropriate reference. We have accordingly replaced the original reference with the reference #2 for the paper published in 2019. 5. The manuscript needs scientific writing with no repetition of sentences to maintain proper connectivity and flow of information. I apologize for the repetition of some sentences. In view of your comment, we have accordingly revised the manuscript. 6. Citations in the manuscript do not look appropriate as all the citations are placed after the period, which need to be corrected. I apologize for this. As per your advice, we have corrected this matter in the revised manuscript, and all reference citations are now placed before the period or comma. Specific comments: 1. Line 24-25; modify as “All of the other authors contributed to sample collection, data collection and interpretation, and manuscript review”. In accordance with the reviewer’s suggestion, we have revised the manuscript as follows: Title page, lines 24–25 “All of the other authors contributed to sample collection, data collection and interpretation, and manuscript review.” 2. Line 240 and 356; patients without……….need to be elaborated. Based on the reviewer’s suggestion, we have revised the manuscript as follows: Results section, lines 239–240 “These 8 patients without KRAS mutation detected by RASKET showed the presence of KRAS mutations by ddPCR.” Results section, lines 325 “hence, we re-evaluated the outcome by comparing patients with emergence of ctDNA within 1 year to patients without emergence.” 3. Line 255-257; Highlighted in bold and sentence finished abruptly………….correction required. In accordance with the reviewer’s suggestion, we have revised the manuscript as follows: Results section, lines 253–255: “One-point assessment of KRAS ctDNA and CA19-9 levels before surgery was not associated with RFS, but KRAS ctDNA before chemotherapy was a potential predictive prognostic factor, whereas CA19-9 prior to chemotherapy was not” 4. All figure legends are inserted in the main text. Please submit the separate file for figure legends. I apologize for the inappropriate insertion of figure legends in the main text. Figure legends have now been placed at the end of the manuscript. 5. Line 364-365; remove the bold font and put a period at the end of the sentence. As per the reviewer’s suggestion, we have revised the relevant text in the manuscript as follows: Results section, lines 329–330: “Sequential assessments of ctDNA within 6 months to assess therapeutic responses of chemotherapy-naïve patients 6. Pancreatic cancer has been used multiple time and it could be abbreviated as PC. In view of the reviewer’s comment, we have replaced the term “pancreatic cancer” in the text with the abbreviation “PDAC.” 7. Line 412-415; sentence has been repeated, correction needed. I apologize for the repeated sentence. We have accordingly deleted this in the manuscript as follows: Discussion section, lines 373 “reported that one-point assessment of ctDNA before surgery was associated with patient outcome.” 8. Line 441-444; sentence has been repeated, correction needed. We did not identify any repeated sentence in lines 441–444. 9. There are relevant and recent references are missed by the authors therefore, references need to be updated. I apologize for the inappropriate references. In view of the reviewer’s comment, we have accordingly checked all references and appropriately updated them. 10. Figure 2; better resolution is required so that in print form, it should be readable. In accordance with the reviewer’s advice, we have replaced the figure with Figure 2 with better resolution. 11. Supporting information; sentences are not ending with the period, written casually. Please revise the supporting information. I apologize for this. We have accordingly revised the sentences in view of your comment. 12. Figure legends: Figure legends are not correctly written. X-and Y-axes are not defined in the legends and there is no statistical information mentioned in the legends. In accordance with the reviewer’s comment, we have revised the figure legends and defined the X- and Y-axes. 13. For data reproducibility, authors have not mentioned how many times the experiments were repeated to get the statistical significance. While writing the figure legends, please mention how many times the experiment were repeated with their statistical significance. In view of the reviewer’s comment, we have added the following text in the Methods section: Lines 194–195: “For data reproducibility, analysis of KRAS status in tumor tissues and plasma was performed in duplicate or triplicate.” Submitted filename: Response_to_Reviewers_Watanabe_L5.docx Click here for additional data file. 18 Dec 2019 Longitudinal monitoring of KRAS-mutated circulating tumor DNA enables the prediction of prognosis and therapeutic responses in patients with pancreatic cancer PONE-D-19-17596R1 Dear Dr. Suzuki, We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements. Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication. Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. With kind regards, Surinder K. Batra Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Dear Editor, Authors have revised the manuscript and addressed all the concerns/comments raised during the review. My reviews for the revised manuscript are as following: 1. Authors have addressed most of the comments and highlighted the novelty of the work in the revised manuscript. 2. Reference citation and language of the manuscript is acceptable for publishing this work in PLOS One. 3. Authors could have modified abstract to a better extent to avoid repetition from their previous abstract publication in JCO. 4. Figures have been revised and submitted by authors with a better resolution and readable text/legend. My recommendation to the editor is that manuscript should be considered for publication in PLOS One. Reviewer #2: (No Response) ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No 20 Dec 2019 PONE-D-19-17596R1 Longitudinal monitoring of KRAS-mutated circulating tumor DNA enables the prediction of prognosis and therapeutic responses in patients with pancreatic cancer Dear Dr. Suzuki: I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. For any other questions or concerns, please email plosone@plos.org. Thank you for submitting your work to PLOS ONE. With kind regards, PLOS ONE Editorial Office Staff on behalf of Prof. Surinder K. Batra Academic Editor PLOS ONE
  43 in total

Review 1.  Circulating Tumor Cells and Cell-Free DNA in Pancreatic Ductal Adenocarcinoma.

Authors:  Tamara M H Gall; Samuel Belete; Esha Khanderia; Adam E Frampton; Long R Jiao
Journal:  Am J Pathol       Date:  2019-01       Impact factor: 4.307

2.  Heterogeneity of KRAS Mutations in Pancreatic Ductal Adenocarcinoma.

Authors:  Daisuke Hashimoto; Kota Arima; Naomi Yokoyama; Akira Chikamoto; Katsunobu Taki; Risa Inoue; Takayoshi Kaida; Takaaki Higashi; Hidetoshi Nitta; Masaki Ohmuraya; Masahiko Hirota; Toru Beppu; Hideo Baba
Journal:  Pancreas       Date:  2016-09       Impact factor: 3.327

3.  Plasma cell-free DNA in ovarian cancer: an independent prognostic biomarker.

Authors:  Aparna A Kamat; Mathew Baldwin; Diana Urbauer; Diana Dang; Liz Y Han; Andrew Godwin; Beth Y Karlan; Joe L Simpson; David M Gershenson; Robert L Coleman; Farideh Z Bischoff; Anil K Sood
Journal:  Cancer       Date:  2010-04-15       Impact factor: 6.860

4.  CA19-9 in potentially resectable pancreatic cancer: perspective to adjust surgical and perioperative therapy.

Authors:  Werner Hartwig; Oliver Strobel; Ulf Hinz; Stefan Fritz; Thilo Hackert; Constanze Roth; Markus W Büchler; Jens Werner
Journal:  Ann Surg Oncol       Date:  2012-12-18       Impact factor: 5.344

Review 5.  Preoperative/neoadjuvant therapy in pancreatic cancer: a systematic review and meta-analysis of response and resection percentages.

Authors:  Sonja Gillen; Tibor Schuster; Christian Meyer Zum Büschenfelde; Helmut Friess; Jörg Kleeff
Journal:  PLoS Med       Date:  2010-04-20       Impact factor: 11.069

6.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

7.  Repeated mutKRAS ctDNA measurements represent a novel and promising tool for early response prediction and therapy monitoring in advanced pancreatic cancer.

Authors:  S Kruger; V Heinemann; C Ross; F Diehl; D Nagel; S Ormanns; S Liebmann; I Prinz-Bravin; C B Westphalen; M Haas; A Jung; T Kirchner; M von Bergwelt-Baildon; S Boeck; S Holdenrieder
Journal:  Ann Oncol       Date:  2018-12-01       Impact factor: 32.976

8.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing.

Authors:  Marco Gerlinger; Andrew J Rowan; Stuart Horswell; James Larkin; David Endesfelder; Eva Gronroos; Pierre Martinez; Nicholas Matthews; Aengus Stewart; Charles Swanton; M Math; Patrick Tarpey; Ignacio Varela; Benjamin Phillimore; Sharmin Begum; Neil Q McDonald; Adam Butler; David Jones; Keiran Raine; Calli Latimer; Claudio R Santos; Mahrokh Nohadani; Aron C Eklund; Bradley Spencer-Dene; Graham Clark; Lisa Pickering; Gordon Stamp; Martin Gore; Zoltan Szallasi; Julian Downward; P Andrew Futreal
Journal:  N Engl J Med       Date:  2012-03-08       Impact factor: 91.245

9.  The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers.

Authors:  Luis A Diaz; Richard T Williams; Jian Wu; Isaac Kinde; J Randolph Hecht; Jordan Berlin; Benjamin Allen; Ivana Bozic; Johannes G Reiter; Martin A Nowak; Kenneth W Kinzler; Kelly S Oliner; Bert Vogelstein
Journal:  Nature       Date:  2012-06-28       Impact factor: 49.962

10.  Prognostic value of circulating tumour DNA in patients undergoing curative resection for pancreatic cancer.

Authors:  Naoto Hadano; Yoshiaki Murakami; Kenichiro Uemura; Yasusi Hashimoto; Naru Kondo; Naoya Nakagawa; Taijiro Sueda; Eiso Hiyama
Journal:  Br J Cancer       Date:  2016-06-09       Impact factor: 7.640

View more
  18 in total

1.  Splenic non-infarction volume determines a clinically significant hepatic venous pressure gradient response to partial splenic embolization in patients with cirrhosis and hypersplenism.

Authors:  Tsuyoshi Ishikawa; Ryo Sasaki; Tatsuro Nishimura; Takashi Matsuda; Takuya Iwamoto; Issei Saeki; Isao Hidaka; Taro Takami; Isao Sakaida
Journal:  J Gastroenterol       Date:  2021-02-24       Impact factor: 7.527

Review 2.  Circulating Tumor Cells, Circulating Tumor DNA and Other Blood-based Prognostic Scores in Pancreatic Ductal Adenocarcinoma - Mini-Review.

Authors:  Marian Liberko; Katarina Kolostova; Arpad Szabo; Robert Gurlich; Martin Oliverius; Renata Soumarova
Journal:  In Vivo       Date:  2021 Jan-Feb       Impact factor: 2.155

Review 3.  Current and Emerging Applications of Droplet Digital PCR in Oncology: An Updated Review.

Authors:  Susana Olmedillas-López; Rocío Olivera-Salazar; Mariano García-Arranz; Damián García-Olmo
Journal:  Mol Diagn Ther       Date:  2021-11-13       Impact factor: 4.074

Review 4.  Circulating tumour DNA: a challenging innovation to develop "precision onco-surgery" in pancreatic adenocarcinoma.

Authors:  Daniel Pietrasz; Elisabetta Sereni; Francesco Lancelotti; Antonio Pea; Claudio Luchini; Giulio Innamorati; Roberto Salvia; Claudio Bassi
Journal:  Br J Cancer       Date:  2022-02-23       Impact factor: 9.075

5.  Detection of Circulating Tumor DNA in Patients with Pancreatic Cancer Using Digital Next-Generation Sequencing.

Authors:  Anne Macgregor-Das; Jun Yu; Koji Tamura; Toshiya Abe; Masaya Suenaga; Koji Shindo; Michael Borges; Chiho Koi; Shiro Kohi; Yoshihiko Sadakari; Marco Dal Molin; Jose A Almario; Madeline Ford; Miguel Chuidian; Richard Burkhart; Jin He; Ralph H Hruban; James R Eshleman; Alison P Klein; Christopher L Wolfgang; Marcia I Canto; Michael Goggins
Journal:  J Mol Diagn       Date:  2020-03-20       Impact factor: 5.568

Review 6.  Clinical implementation and current advancement of blood liquid biopsy in cancer.

Authors:  Kazunori Watanabe; Yusuke Nakamura; Siew-Kee Low
Journal:  J Hum Genet       Date:  2021-06-04       Impact factor: 3.172

Review 7.  Mutations in key driver genes of pancreatic cancer: molecularly targeted therapies and other clinical implications.

Authors:  Hai-Feng Hu; Zeng Ye; Yi Qin; Xiao-Wu Xu; Xian-Jun Yu; Qi-Feng Zhuo; Shun-Rong Ji
Journal:  Acta Pharmacol Sin       Date:  2021-02-11       Impact factor: 7.169

8.  Prognostic value of circulating tumor DNA in pancreatic cancer: a systematic review and meta-analysis.

Authors:  Zengli Fang; Qingcai Meng; Bo Zhang; Si Shi; Jiang Liu; Chen Liang; Jie Hua; Xianjun Yu; Jin Xu; Wei Wang
Journal:  Aging (Albany NY)       Date:  2020-12-09       Impact factor: 5.682

9.  Transcriptomic Profiling Identifies an Exosomal microRNA Signature for Predicting Recurrence Following Surgery in Patients with Pancreatic Ductal Adenocarcinoma.

Authors:  Satoshi Nishiwada; Ya Cui; Masayuki Sho; Eunsung Jun; Takahiro Akahori; Kota Nakamura; Fuminori Sonohara; Suguru Yamada; Tsutomu Fujii; In Woong Han; Susan Tsai; Yasuhiro Kodera; Joon Oh Park; Daniel Von Hoff; Song Cheol Kim; Wei Li; Ajay Goel
Journal:  Ann Surg       Date:  2021-06-16       Impact factor: 12.969

Review 10.  Impact of circulating tumor DNA in hepatocellular and pancreatic carcinomas.

Authors:  Sameer A Dhayat; Zixuan Yang
Journal:  J Cancer Res Clin Oncol       Date:  2020-04-27       Impact factor: 4.553

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.